Computed Tomography (CT)
Computed Tomography (CT) is a diagnostic imaging modality that produces three dimensional (3D) images of the body by making multiple x-ray exposures at different locations around the patient. The basic system comprising a CT scanner as well known in the art includes a scanning gantry, x-ray generator, computer system, viewing and operator consoles, and a hard copy camera, all as shown in FIG. 11. The scanning gantry as well known in the art contains an x-ray tube, collimator, detector array, and associated data acquisition electronics. The CT scanning process involves collecting raw projection data by means of projecting highly collimated x-rays across a patient from different orientations. From these raw projection data (the sinogram), the internal structure of the object can be computed by various reconstruction schemes [Kak & Slaney]. Because of its medical utility, the use of CT imaging continues to grow, and with it the amount of patient data that must be handled, transmitted and stored.
Advances in CT Technology
Recent advances in technology, such as helical or spiral scanning with slip-ring design [Crawford] and multirow detector technology, enable faster scanning of more patients and larger volumes for each patient. A slip-ring technology allows continuous rotation of the x-ray tube and detector array assembly. Spiral CT has reduced scan times and allowed for continuous data acquisition for volumetric medical imaging. Because the raw data are acquired in a continuous fashion in spiral CT, any transverse slice can be specified for reconstruction at any longitudinal interval of scanning. These images generated with a small reconstruction increment provide overlapping image slices and thus improve both for high- and low-contrast resolution [Kalender et al.]. Improving longitudinal resolution due to overlapping reconstruction is important for volumetric imaging, as the in-plane resolution is usually much higher (on the order of 5-10) than the longitudinal resolution. For example, high-resolution CT images of the cochlea are obtained by scanning the cochlea and temporal bone with 1 mm collimation but reconstructing images at every 0.1 mm. In general, a higher image resolution provides a better diagnosis and finer assessment of small structures such as a stenosis in a vessel. Thin slice volume scanning is particularly useful for virtual colonoscopy and CT angiography. Thus, there is a trend to conduct higher resolution tomography which increases the amount of data to be handled and stored.
A recent development in technology is the introduction of multirow detector CT scanners. Instead of the 1-dimensional detectors, these scanners use 2-dimensional detectors that consist of several arrays of detectors. Thus, when using a scanner having n detector arrays, the volume scan time T to obtain the same amount of data is reduced to roughly T/n. In addition, the x-ray tube's output can be more efficiently used.
Increase in CT Data
Data volumes have increased tremendously with new faster and finer CT scanners. In order to handle the large data volumes, advances in computer technology and storage devices are necessary. In addition, advances in digital technology and algorithm development allow interactive and more thorough display of patient image data by physicians and radiologists, for example in Picture Archiving and Communication Systems (PACS) or with Computer Aided Diagnosis (CAD). Thus, the volume of CT digital data that must be accommodated is constantly increasing, and expected to continue increasing. In the prior art, CT images were printed on laser film, viewed on a light box, and stored in film folders in a film library. However, the costs for manual labor, propensity to misplace films, and need to distribute images to multiple caregivers in different locations has motivated the development of PACS. A serious challenge to implementing PACS is the amount of data that must be accommodated. CT images typically consist of 512 by 512 pixels, with 12 bits of gray scale resolution, so each image is about 0.5 MB (4,000,000 bits) in size. There may be 100-200 images for each patient study, so the complete data set may reach more than 100 MB. Because of this large size, digital data sets representing images are usually only temporarily saved, with the ultimate record of patient images being the physical film copy. However, the advent of digital systems is making the storage of digital image data more compelling. Also, as computers become less expensive and more powerful, it is possible to have distributed workstations to reconstruct images from raw data for diagnostic viewing. In this case, large data files must be transmitted across the network, requiring waits of long duration. Decreasing the size of files to be transmitted would increase system performance.
Advantages of Storing Raw Data Rather Than Image Data
One of the important features of spiral CT is that retrospective reconstruction can be performed. Spiral raw data are collected at first and stored instead of reconstructed images. Then, these raw data can be recalled later to generate images with different reconstruction increments depending on clinical applications. Similarly, in a multirow spiral CT, images with different slice thickness can be generated from the same set of raw data, depending on clinical applications. Thus, there is a need in the art, and a perceived benefit, for storing raw data as it allows a medical professional to revisit not only the same images previously used (by saving the particular index identifying the views then reviewed), but also to consider the additional input of views not previously considered which can be freshly constructed from the raw data. This can help a medical professional giving a second opinion, the same medical professional who might want to reconsider his original opinion, or even to possibly do other diagnoses from data not previously considered or relating to the prior medical symptom. However, despite these added benefits of having original raw data, present practice is to save only the image data and the raw data are deleted at the time of image data archival, as the raw data is typically 3-6 times larger than the image data for a given slice coverage. For example, for a chest CT examination to cover 30 cm with 1 mm collimation and 1.5 table increment, the size of raw data is 400 MB, while the size of 60 images with 5 mm slice thickness is 30 MB. Thus, the trend in the prior art is to focus on starting with the image data and then to work on finding better ways to save or store it as the overwhelming crush of image data alone is generally considered monumental so that those of skill in the art don't seek to compound the problem by choosing an inherently larger data set to begin with.
Prior Art Image Data Compression
Methods considered in the prior art for reducing the amount of data to be handled and stored include image data compression; using transformations and encoding to represent image information with fewer bits [Rabbani and Jones]. Many schemes have been attempted to do this [Foos]. One class of algorithms, called lossless, produces no change in the final data. However, because of the information content (entropy) of the image, compression ratios achieved by this technique are typically in the range of 2-3 to 1 and are thus of limited value. Techniques that allow differences between the original and reconstructed compressed image can reach much higher compression ratios, with more compression generally resulting in higher distortion of the final image upon recall. Studies have shown that recalled CT images with compression ratios in the range of 8:1 have observable distortions, which may affect the confidence of the interpretation by radiologists. In the present legal and medical environment, such levels of compression are thus not practical as in many cases the true value of image storage is to accurately reproduce what the medical professional made reference to when the initial diagnosis was made. Introducing artifacts into the recalled image interferes with this purpose which may even defeat the value of storing any particular image.
Under present prior art medical practice, the original raw projection data that is used to reconstruct image slices is routinely kept for only a day or so, in case further views are needed for diagnosis. The size of the projection data can be quite large, as each measurement involves approximately 1000 detectors, with tens of thousands of measurements across the volume, resulting in data sizes of 100 MB per patient. In fact, the size of the projection data is usually as large or larger than the total reconstructed image slices. Therefore, it is not normally saved with the digital image data for a typical clinical examination except for special research purposes.
Thus there is a long felt need to more effectively manage digital data for CT imaging in general, and a teaching in the prior art that compressing image digital data is the only option to reduce the size of the data to be saved.